Machine Learning

How to Difference a Time Series Dataset with Python

Last Updated on August 14, 2020

Differencing is a popular and widely used data transform for time series.

In this tutorial, you will discover how to apply the difference operation to your time series data with Python.

After completing this tutorial, you will know:

  • About the differencing operation, including the configuration of the lag difference and the difference order.
  • How to develop a manual implementation of the differencing operation.
  • How to use the built-in Pandas differencing function.

Kick-start your project with my new book Time Series Forecasting With Python, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

  • Updated Apr/2019: Updated the link to dataset.
How to Difference a Time Series Dataset with Python

How to Difference a Time Series Dataset with Python
Photo by Marcus, some rights reserved.

Why Difference Time Series Data?

Differencing is a method of transforming a time series dataset.

It can be used to remove the series dependence on time, so-called temporal dependence. This includes structures like trends and seasonality.

Differencing can help stabilize
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